It is very challenging to choose between the three biggest cloud providers – Amazon Web Services (AWS), Microsoft Azure and Google Cloud Platform (GCP). The best part is they all offer a free tier for spinning up an instance and trying out the platform before one buys. Many organizations look out for multiple cloud vendors (AWS vs Azure vs Google Cloud) that can help them avoid lock-in with one of the big three or even get benefits from the unique capabilities of each platform, mostly while experimenting with AI and machine learning.

The free tier facility helps the users to first test out the capabilities of each platform to meet their business demands and then wisely choose which one to continue. This model has been introduced by AWS web services and later on adopted by both its leading rivals to attract developers to their cloud platforms.

Though various organizations are utilizing multiple capabilities from different cloud service providers (CSP), there exist some dimensions that cross-identifies the high-quality services from each of the CSPs through comparative analysis.

Let us discuss these parameters which help you weigh your application or workload requirements so that you can easily select the best fit for your business.

AWS: Initially, AWS web services introduced their Elastic Compute Cloud (EC2) model that facilitates a core compute service to allow users to configure virtual machines using either pre-configured or custom Amazon Machine Images (AMIs).W Users can easily select the size, power, memory capacity, and number of VMs along with different regions and availability zones to launch the instances. The EC2 model allows load balancing, known as Elastic Load Balancing (ELB), and auto-scaling. The ELB model distributes uniform loads across instances to boost up the performance and auto-scaling helps to automatically scale the available EC2 capacity up or down.

Microsoft Azure: Microsoft Azure introduced their compute service in 2012 and made it generally available in May 2013. A Virtual Hard disk (VHD) is chosen by Azure users that are perceived equivalent to Amazon’s AMI. This VHD helps the users to create a virtual machine. The VHD can be either user-defined or can be predefined by Microsoft or any of its third party. The user needs to specify the number of cores and amount of memory with each VM involved.

Google Cloud: The Google Compute Engine (GCE) was introduced in 2012 that allows the users to launch virtual machines just like AWS web services, into different regions and availability groups. Later in 2013, Google released the general availability of GCE with added enhancements such as load balancing, extended support for operating systems, live migration of VMs, fast and persistent disks and multi-core instances.

Storage and Databases – AWS vs Azure vs Google Cloud

AWS: A temporary storage is provided by AWS cloud consulting services which are allocated while deploying the instance and is destroyed after terminating it. AWS offers block storage that can either be attached to any instances or can be kept separate just like hard disks. AWS cloud consulting services offers S3 services and Glacier storage for object storage and archive storage respectively. AWS cloud consulting services extends full support to relational, NoSQL databases and Big Data.

Azure: Azure avails temporary storage (D drive) and Page Blobs- a block storage option from Microsoft as a storage alternative to its users. For Object storage, Azure uses Block Blobs and File Serve. Both relational and NoSQL databases and Big Data are supported by Azure using Windows Azure Table and HDInsight.

Google Cloud: Both temporary storage and persistent disks option are provided by GCP as a storage alternative. For Object storage, a Google Cloud Storage is offered by GCP and also the GCP supports relational databases through Google Cloud SQL. Technologies such as Big Query, Big Table, and Hadoop are developed and fully supported by Google. Although Google’s Nearline offers cheap archiving just as Glacier, it lacks latency on recovery.

Networking – AWS vs Azure vs Google Cloud

Amazon offers Virtual Private Clouds (VPCs) and Azure offers Virtual Network (VNET) that works in a similar manner and allows users to collate VMs into isolated networks in the cloud. Users are allowed to define a network topology, create subnets, route tables, state private IP address ranges, and network gateways using VPCs and VNETs. They both have solutions to extend the user’s on-premise data center into the public or even hybrid cloud.

Whereas, the Google Compute Engine instance belongs to a single network that helps in defining the address range and gateway address for all instances connected to it. Users can apply Firewall rules to an instance, and it can receive a public IP address.

There are other factors too to compare these three cloud services giants such as support levels, management, security, and access. If you wish to avail cloud services, i2k2 Networks is a one-stop destination that offers state-of-the-art public cloud services and solutions. We offer managed public, private and hybrid cloud solution along with full control over your data as an added advantage. Our customer-centric integration, API, and 24 hours technical support assist the users during cloud migration and data backup and recovery. You can contact us at +91-120-466-3031 | +91-9711774040 or can fill out our contact form.